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Missing Pieces of the Puzzle
EE122 Fall 2011
Scott Shenkerhttp://inst.eecs.berkeley.edu/~ee122/
Materials with thanks to Jennifer Rexford, Ion Stoica, Vern Paxsonand other colleagues at Princeton and UC Berkeley
Announcements• Everyone should be signed up and have account
– If you aren’t see me at end of class
• We lost our grader, so delaying HW#2– Gives us a chance to cover more material…
• Beanbags. Really?
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Agenda for Today• Finish up routing: not as simple as you might think• Discuss missing pieces: preview of rest of class
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Last Time• Link-State Routing• Spread state everywhere• Nodes do local computation over entire graph• Local computation, global state• Doesn’t scale well, involves broadcasts
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This Time• Global computation, local state• We want to limit the distribution of state• So computation must be distributed• The most common example is distance-vector
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Distance-Vector
Details in Section
Distributed Computation of Routes• More scalable than Link-State
– No global flooding
• Each node computing the outgoing port based on:– Local information (who it is connected to)– Paths advertised by neighbors
• Algorithms differ in what these exchanges contain– Distance-vector: just the distance to each destination– Path-vector: the entire path to each destination
• We will focus on distance-vector for now
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Example of Distributed Computation
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I am one hop away
I am one hop away
I am one hop away
I am two hops away
I am two hops away
I am two hops away
I am two hops awayI am three hops away
I am three hops away
DestinationI am three hops away
Very similar to Monday’s Class• Destination stands up• Announces neighbors
– They stand up
• They announce their neighbors– They stand up
• …..and so on, until source stands• On Monday you started with the source, but paths
are reversible so it doesn’t matter….• Key point: don’t stand up twice!
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Step 1• Destination stands up
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Step 1
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Step 2• Destination stands up• Announces neighbors
– They stand up
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Step 2
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I am one hop away
I am one hop away
I am one hop away
Step 3• Destination stands up• Announces neighbors
– They stand up
• They announce their neighbors– They stand up
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Step 3
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I am two hops away
I am two hops away
I am two hops away
I am two hops away
Why Not Stand Up Twice?• Being called a second time means that there is a
second (and longer) path to you– You already contacted your neighbors the first time– Your distance to destination is based on shorter path
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Basics of Distributed Routing• Nodes advertise their best paths to neighbors• Nodes select among paths offered by neighbors
– Ignore all but the best path
• Iterative process eventually leads to convergence• If “cost” is hopcounts, then nodes find out about
shortest paths first (ignore later ones)– If costs are general, later paths might be better
• Remember: nodes “select” among offered paths– But what selection criteria are allowed?
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No agreement on metrics?• If the nodes choose their paths according to
different criteria, then bad things might happen• Example
– Node A is minimizing latency– Node B is minimizing loss rate– Node C is minimizing price
• Any of those goals are fine, if globally adopted– Only a problem when nodes use different criteria
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What Happens Here?
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Low price link
Low loss link
Low delay linkLow loss link
Low delay linkLow price link
Cares about price, then loss
Cares about delay,then price
Cares about loss,then delay
Can You Use Any Metric?• Are there any metrics that won’t work, even if
everyone agrees on it?• What about maximizing capacity?
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What Happens Here?
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All nodes want to maximize capacityA high capacity link gets reduced to low capacity
Must agree on loop-avoiding metric• When all nodes minimize same metric• And that metric increases around loops• Then process is guaranteed to converge
• On to the details of the algorithm….– Nothing interesting, but will be on test.
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Distance Vector Routing• Each router knows the links to its neighbors
– Does not flood this information to the whole network
• Each router has provisional “shortest path”– E.g.: Router A: “I can get to router B with cost 11 via
next hop router D”
• Routers exchange this Distance-Vector information with their neighboring routers– Vector because one entry per destination
• Routers update their idea of the best path using info from neighbors
• Iterative process converges to set of shortest paths
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Information Flow in Distance Vector
Host A
Host BHost E
Host D
Host C
N1 N2
N3
N4
N5
N7N6
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Information Flow in Distance Vector
Host A
Host BHost E
Host D
Host C
N1 N2
N3
N4
N5
N7N6
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Information Flow in Distance Vector
Host A
Host BHost E
Host D
Host C
N1 N2
N3
N4
N5
N7N6
Why is this different from flooding?
Bellman-Ford Algorithm• INPUT:
– Link costs to each neighbor– Not full topology
• OUTPUT:– Next hop to each destination and the corresponding cost– Does not give the complete path to the destination
• My neighbors tell me how far they are from dest’n– Compute: (cost to nhbr) plus (nhbr’s cost to destination)– Pick minimum as my choice– Advertise that cost to my neighbors
• Next few slides show the corrosive power of ppt27
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Bellman-Ford - Overview• Each router maintains a table
– Best known distance from X to Y, via Z as next hop = DZ(X,Y)
• Each local iteration caused by: – Local link cost change – Message from neighbor
• Notify neighbors only if least cost path to any destination changes– Neighbors then notify their neighbors if
necessary
wait for (change in local link cost or msg from neighbor)
recompute distance table
if least cost path to any dest has changed, notify neighbors
Each node:
Bellman-Ford - Overview• Each router maintains a table
– Row for each possible destination– Column for each directly-attached
neighbor to node– Entry in row Y and column Z of node X
best known distance from X to Y, via Z as next hop = DZ(X,Y)
A C12
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B D3
1
B CB 2 8C 3 7D 4 8
Node A
Neighbor (next-hop)
Destinations DC(A, D)
Bellman-Ford - Overview• Each router maintains a table
– Row for each possible destination– Column for each directly-attached
neighbor to node– Entry in row Y and column Z of node X
best known distance from X to Y, via Z as next hop = DZ(X,Y)
A C12
7
B D3
1
B CB 2 8C 3 7D 4 8
Node A
Smallest distance in row Y = shortestDistance of A to Y, D(A, Y)
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Distance Vector Algorithm (cont’d)
1 Initialization: 2 for all neighbors V do3 if V adjacent to A 4 D(A, V) = c(A,V);5 else 6 D(A, V) = ∞;7 send D(A, Y) to all neighbors loop: 8 wait (until A sees a link cost change to neighbor V /* case 1 */9 or until A receives update from neighbor V) /* case 2 */10 if (c(A,V) changes by ±d) /* case 1 */11 for all destinations Y that go through V do 12 DV(A,Y) = DV(A,Y) ± d 13 else if (update D(V, Y) received from V) /* case 2 */ /* shortest path from V to some Y has changed */ 14 DV(A,Y) = DV(A,V) + D(V, Y); /* may also change D(A,Y) */15 if (there is a new minimum for destination Y)16 send D(A, Y) to all neighbors 17 forever
• c(i,j): link cost from node i to j• DZ(A,V): cost from A to V via Z• D(A,V): cost of A’s best path to V
Example:1st Iteration (C A)
A C12
7
B D3
1
B CB 2 8C ∞ 7D ∞ 8
Node A
A C DA 2 ∞ ∞C ∞ 1 ∞D ∞ ∞ 3
Node B
Node C
A B DA 7 ∞ ∞B ∞ 1 ∞D ∞ ∞ 1
B CA ∞ ∞B 3 ∞C ∞ 1
Node D7 loop: …13 else if (update D(A, Y) from C) 14 DC(A,Y) = DC(A,C) + D(C, Y);15 if (new min. for destination Y)16 send D(A, Y) to all neighbors 17 forever
DC(A, B) = DC(A,C) + D(C, B) = 7 + 1 = 8
DC(A, D) = DC(A,C) + D(C, D) = 7 + 1 = 8
Example: 1st Iteration (B A)
A C12
7
B D3
1
B CB 2 8C 3 7D 5 8
Node A
A C DA 2 ∞ ∞C ∞ 1 ∞D ∞ ∞ 3
Node B
Node C
A B DA 7 ∞ ∞B ∞ 1D ∞ ∞ 1
Node D7 loop: …13 else if (update D(A, Y) from B) 14 DB(A,Y) = DB(A,B) + D(B, Y);15 if (new min. for destination Y)16 send D(A, Y) to all neighbors 17 forever
DB(A, C) = DB(A,B) + D(B, C) = 2 + 1 = 3
DB(A, D) = DB(A,B) + D(B, D) = 2 + 3 = 5
B CA ∞ ∞B 3 ∞C ∞ 1
Example: End of 1st Iteration
A C12
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B D3
1
B CB 2 8C 3 7D 5 8
Node A Node B
Node C
A B DA 7 3 ∞B 9 1 4D ∞ 4 1
Node D
B CA 5 8B 3 2C 4 1
End of 1st Iteration All nodes knows the best two-hop
paths
A C DA 2 8 ∞C 9 1 4D ∞ 2 3
Example: 2nd Iteration (A B)
A C12
7
B D3
1
B CB 2 8C 3 7D 5 8
Node A Node B
Node C
A B DA 7 3 ∞B 9 1 4D ∞ 4 1
Node D
B CA 5 8B 3 2C 4 1
A C DA 2 3 ∞C 5 1 4D 7 2 3
7 loop: …13 else if (update D(B, Y) from A) 14 DA(B,Y) = DA(B,A) + D(A, Y);15 if (new min. for destination Y)16 send D(B, Y) to all neighbors 17 forever
DA(B, C) = DA(B,A) + D(A, C) = 2 + 3 = 5
DA(B, D) = DA(B,A) + D(A, D) = 2 + 5 = 7
Where does this 5 come from?Where does this 7 come from?What harm does this cause?How could we fix this?
Example: End of 2nd Iteration
A C12
7
B D3
1
B CB 2 8C 3 7D 4 8
Node A
A C DA 2 3 11C 5 1 4D 7 2 3
Node B
Node C
A B DA 7 3 6B 9 1 4D 12 4 1
Node D
B CA 5 4B 3 2C 4 1
End of 2nd Iteration All nodes knows the best three-hop paths
Example: End of 3rd Iteration
A C12
7
B D3
1
B CB 2 8C 3 7D 4 8
Node A
A C DA 2 3 6C 5 1 4D 7 2 3
Node B
Node C
A B DA 7 3 5B 9 1 4D 11 4 1
Node D
B CA 5 4B 3 2C 4 1
End of 2nd Iteration: Algorithm
Converges!
Intuition• Initial state: best one-hop paths• One round: best two-hop paths• Two rounds: best three-hop paths• …• Kth round: best (k+1) hop paths
• This must eventually converge….but how does it respond to changes in cost?
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Distance Vector: Link Cost Changes
A C14
50
B1
“goodnews travelsfast”
A CA 4 6C 9 1
Node B
A BA 50 5B 54 1
Node C
Link cost changes heretime
Algorithm terminates
loop: 8 wait (until A sees a link cost change to neighbor V9 or until A receives update from neighbor V) /10 if (c(A,V) changes by ±d) /* case 1 */11 for all destinations Y that go through V do 12 DV(A,Y) = DV(A,Y) ± d 13 else if (update D(V, Y) received from V) /* case 2 */14 DV(A,Y) = DV(A,V) + D(V, Y); 15 if (there is a new minimum for destination Y)16 send D(A, Y) to all neighbors 17 forever
A CA 1 6C 9 1
A BA 50 5B 54 1
A CA 1 6C 9 1
A BA 50 2B 51 1
A CA 1 3C 3 1
A BA 50 2B 51 1
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DV: Count to Infinity Problem
A C14
50
B60
“badnews travelsslowly”
Node B
Node C
Link cost changes here time
…
loop: 8 wait (until A sees a link cost change to neighbor V9 or until A receives update from neighbor V) /10 if (c(A,V) changes by ±d) /* case 1 */11 for all destinations Y that go through V do 12 DV(A,Y) = DV(A,Y) ± d 13 else if (update D(V, Y) received from V) /* case 2 */14 DV(A,Y) = DV(A,V) + D(V, Y); 15 if (there is a new minimum for destination Y)16 send D(A, Y) to all neighbors 17 forever
A CA 4 6C 9 1
A BA 50 5B 54 1
A CA 60 6C 9 1
A BA 50 5B 54 1
A CA 60 6C 9 1
A BA 50 7B 101 1
A CA 60 8C 9 1
A BA 50 7B 101 1More like avoidance: believe
anything if it hides the bad news
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Distance Vector: Poisoned Reverse
A C14
50
B60• If B routes through C to get to A:
- B tells C its (B’s) distance to A is infinite (so C won’t route to A via B)
Node B
Node C
Link cost changes here; C updates D(C, A) = 60 as B has advertised D(B, A) = ∞
timeAlgorithm terminates
A CA 4 6C 9 1
A BA 50 5B ∞ 1
A CA 60 6C 9 1
A BA 50 5B ∞ 1
A CA 60 6C 9 1
A BA 50 ∞B ∞ 1
A CA 60 51C 9 1
A BA 50 ∞B ∞ 1
A CA 60 51C 9 1
A BA 50 ∞B ∞ 1
Will PR Solve C2I Problem Completely?
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A C1
B
D
1
1 11 1
2 2
∞
∞ ∞
100
100 1003
∞
4
∞ 4
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Another Distributed Loop Avoidance• Exchange entire paths, not just cost of paths
– My path to the destination is <n1, n2, n3, …>– Path-vector routing (PV)
• Nodes can use arbitrary metrics to choose paths– No need to agree on single metric– Each node can evaluate the path independently
• No loops, but algorithm might not converge
• Previous example of multiple criteria showed this 43
Scary Thought• The Internet’s interdomain routing is based on PV• Domains can use arbitrary criteria to choose paths• There is no guarantee that the entire Internet
routing system won’t oscillate• We’ve just been “lucky” so far….
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Another Scary Thought• In both DV and PV, what happens when node lies
– UCB’s router says: “Sure, I’m one hop away from MIT”– What happens to traffic destined for MIT?
• This has happened, major outages
• Could this happen with Link-State?
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Routing: Just the Beginning• Link state and distance-vector (and path vector)
are the deployed routing paradigms• But we know how to do much, much better…• Stay tuned for a later lecture where we:
– Reduce convergence time to zero– Respond to failures instantly!
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Missing Pieces
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Where are we?• We have covered the “fundamentals”
– How to deliver packets (routing)– How to build reliable delivery on an unreliable network
• With this, we could build a decent network
• But couldn’t actually do anything with the network– Too many missing pieces
• Today: identify those pieces– Will guide what we cover rest of semester 48
Scenario: Jane Wants Her Music• Jane is sitting in her dorm room, with a laptop
• Has overwhelming urge to listen to John Cage
• What needs to happen to make this possible?
• Go one step at a time
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What Are The Steps Involved?• Accessing the network from laptop
– Wireless or ethernet– Network management (someone needs to make it work)
• Mapping “real world name” to “network name”• Mapping network name to location• Download content from location
– Finding nearby content
• Addressing general security concerns– Verifying that this is the right content– And that no one can tell what she’s downloading
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Access Networks• If access network is “switched”, we understand it
– Just like any other packet-switched network
• If the access network is shared medium, then we need to figure out how to share the medium– Wireless– Classical ethernet
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Media Access Control (MAC)• Carrier sense: (CSMA)
– Don’t send if someone else is sending
• Collision detection: (CD)– Stop if you detect someone else was also sending
• Collision avoidance: (CA)– How to arrange transmissions so that they don’t collide
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Network Management• Control how network interconnects to Internet
– Interdomain routing
• Keep unwanted traffic off network– Firewalls and access control
• Share limited number of public addresses– NAT
• Keep links from overloading– Traffic engineering
Most undeveloped part of the Internet architecture
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Current Network Management• No abstractions, no layers• Just complicated distributed algorithms
– Such as routing algorithms
• Or manual configuration– Such as Access Control Lists and Firewalls
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Future Network Management• Clean abstractions• No complicated distributed algorithms• Treat networks like systems…
Last lecture of class….
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“Real World Name” to “Network Name”• Jane knows what music she wants
• Doesn’t know how to tell network what she wants
• Need to map “real world name” to network name
• Search engine!– Maps keywords to URL
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How can we do this?
Map Network Name to Location• “Name resolution” converts name to location
• We would like location to be nearby copy– Speeds up download – Reduce load on backbone and access networks
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How is this done today?• Name resolution: Domain Name System (DNS)
– Hand in a domain, get back an IP address
• Nearby copy of the data?– CDNs: content distribution networks (like Akamai)
• P2P systems can also point you to nearby content
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Download Data from Location• Need a reliable transfer protocol: TCP
– Must share network with others: congestion control
• But must be able to use URL to retreive content– Need higher-level protocol like HTTP to coordinate
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Ensuring Security• Privacy: prevent sniffers from knowing what she
downloaded (“it was for EE122, I promise!”)• Integrity: ensure data wasn’t tampered with during
its trip through network• Provenance: ensure that music actually came from
the music company (and not some imposter)
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How do we do this today?• Cryptographic measures enable us to do all three• Public Key cryptography is crucial
– No need to share secrets beforehand
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Scenario Requires• Media Access Control• Network management• Naming and name resolution• Content distribution networks• And perhaps P2P• Congestion control• HTTP• Cryptographic measures to secure content
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Rest of Course• Details of IP and TCP
– Bringing reality to general concepts
• Filling in pieces of name resolution and HTTP• Congestion control• Advanced routing• Security• Ethernet and Wireless• Network Management
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